Independent Project

MSc Product Design - Reflection

This year has definitely helped me grow as a design thinker and as a creative. My motivation for undertaking the masters course this year was to encourage me to step outside my comfort zone and create design solutions to problems from a new perspective other than screen based solutions. I feel I have achieved that.

I feel much more comfortable in highlighting where my strengths are after this year - in creative technology both physical and digital. I am looking forward to continuing to blend both aspects in my work, and creste more interactions that encourage and empower people.

This was 5 years well spent at DJCAD, and I’ll be sad to leave but I’ll leave feeling confident in the skills I’ve gained here during my time studying. 

MSc Product Design - Your Supervisor

Your Supervisor is a new building entry system that asks the user to “punch in” when entering the building.

This consents them to being monitored during their time in the building as well as notify users of changes in their “big 5” personality qualities, assigned based on personal data volunteered on social media sites.

Your Supervisor then makes recommendations based on these qualities, all under the guise of providing a better experience for the user using their personal information. 

For this project, I had 3 hand ins to complete:

Creative Output - including Final prototypes:

4 A3 process boards detailing the various stages - Find, Play, Make, Talk:

One process booklet detailing the process from research to final solution:

Overall I'm very happy with everything I've produced - I'm particularly pleased how far my grasp of using creative technology to explore ideas has come, as well as my model making skills (which were not existent at the beginning of this year).

MSc Product Design - (Not Working) Mk. 2

Following Mk. 1 prototype feedback, I went back to explore the front face of the product to give it a more interesting face.

Once again I relied on the laser cutter to create the pieces. This time I did not make the prototype work, as I kept the casing dimensions the same and had already soldered the board from the last prototype.

I was glad I reopened the exploration of the front face as I now have a panel that is much more visually interesting than before. 

I started redefining the speech bubble shape by drawing on inspirations from geometric shapes which created an edgier and visually more interesting shape, as well as drawing inspirations for other products that work with speech in some form. 


I cut several front panels to visualise what these would look like once cut out. I was immediately drawn to the bottom left, which had a megaphone feel to it. 

IMG_1415 2.jpg

Once assembled, there was an immediate difference between the Mk. 1 and Mk. 2 prototype and redesigning the front face was definitely the key. 

MSc Product Design - Working Mk. 1

Following last week's experiment with form, I wanted to achieve a working mk. 1 by the end of the week to finalise the dimensions and get an idea of how everything would fit together. I laser cut the necessary pieces and glued them together layer by layer. Once assembled I integrated the tech and solder the RFID to the board. Overall I was pleased with this prototype as a starting point for moving forward.

MSc Product Design - RFID + Twitter + Text = Profit

Following on from earlier in this week, I wanted to improve on the RFID prototype  - specifically I wanted to explore the possibility of sending a text message when an RFID tag is scanned and also send out a check in tweet.

Since I had the base code and circuit wired up from earlier this week, it was just a matter of implementing the desired features. I played around with several tutorials to try and send SMS messages through Arduino but it was proving difficult without the proper shields attached to the Arduino. This is when I had an idea.

Processing saved the day definitely for this part of the prototype - since it's very easy to connect Arduino to Processing, I could use Processing to handle all the web required functions for the prototype; in this case, interacting with the Twitter API and the Twilio API.


Now when the RFID scanner interacts with the authorised token, it sends a text message to an authorised phone number - mine in this case - and to a Twitter account created so that I didn't spam everyone with test tweets.

This opens up the possibility of allowing the building to text the user when they agree to be monitored by the building and then tweet where the user has just checked in - creating "cookies" for the building. My next steps is to look at what form this product should take.



MSc Product Design - Make Cookies Physical Again!

After a tutorial with Pete Thomas last week, my project took a slight shift in how I planned to raise awareness about the need for privacy to protect personal information. We talked about how the cultural shift towards technology in recent years has made us more neutral to the idea of these technologies gathering information about us. Pete thought that the project would have a bit more weight if it explored how this shift would eventually lead to a loss of personal freedom - for example, how the loss of physical currency in favour of bank cards would have an affect on people. He also thought it'd be interesting to explore how to create physical manifestations of digital behaviour.

I thought about that last part a lot over the weekend and decided to look at how I could use the concept of internet cookies and make that physical. I started by playing around with RFID technology, as I was interested in how I could use that in conjunction with the Twitter qualities from the previous prototype and made a simple circuit that blinked once for an accepted card, and flashed for an unauthorised card.


Next, I did a quick bit of research to see how websites formatted their cookies message that appear when you enter sites for the first time. Most messages were positive and explained that they were gathering the information for the users benefit and to provide them with better experiences. Almost all of them said that if they continued using the site, they agreed to the monitoring, as well as provided a link to explain the cookie policy With this in mine, I wrote my own for DJCAD:


While satisfied with my small scale prototype, I wanted to see what it would look like in proper context - I created a small paper prototype and placed it outside one of the entrances to the Matthew Building. 

This was a dead easy and quick prototype to do to get me thinking about how to physical create a simple digital behaviour. I think this would be something to do as a potential intervention over the coming weeks and and gauge the responses I could get from these signs, if I can get permission from DJCAD. I think it'd be interesting to see what people would do if they felt uncomfortable about the idea of being monitored while in the building but desperately needed in to use the facilities - would people sacrifice the potential information they would give up for the services? 

MSc Product Design - Twitter Personality Texts

Today I spent the day further refining my Twitter application I'd created a few weeks ago. While the badges I'd created yesterday were a good start in displaying that information physically, I wanted to create one of the ideas I had brainstormed on Monday when feeding back to Dean - sending text notifications to the user about their "big 5" qualities. For this, I used the Twilio API, which allows you to buy a number and send text messages through programs created in various coding languages - in my case, Python. 


It was a fairly straightforward process to integrate the API into my code but took a wee bit of tweaking to get the interaction working correctly. I had trouble figuring out how to condense the returned qualities into a string that could then be included in a text but this ended up just involving me converting the list to a string. I also added user input at the beginning of running the app, so that I didn't need to keep going into the Python file itself to swap out the username and phone number. 

Now when I run the app, I still get the usual result in the terminal:

But now it also sends out a text message with the results:


Which is already a much more visually appealing way of viewing the data! It also allows me to use this an interactive prototype with people, even if it is just in it's early stages. I did a quick bit of user testing with members of my family, just to make sure it was texting numbers out with my own verified number:

The results...

The results...

image 2.jpg

Again, I'm going to keep tweaking and adding to this app in the coming weeks - I'll want to use this in a potential workshop later in my process, but would like a refined version for showing off as part of my final hand in. 

MSc Product Design - Twitter Personality Badges

Expanding on the Twitter application I made a few weeks ago, I wanted to explore the concept of what a badge that showcased your Twitter "Big 5" would look like. Using the qualities given to me on one of my tests, I designed a simple badge on Illustrator and cut it using acrylic, to give it a modern feel. The badge is very simple in terms of information: it states the top 5 qualities as well as my Twitter handle. I'm interested in how I could use these badges for a potential workshop later in my play phase on the process, to engage people in conversation about where their specific traits might have come from.

MSc Product Design - Visit from Dean Brown

Yesterday, we were very lucky to be visited by Dean Brown, who spent the day mentoring us and helping us begin the transition from Find into Play. Dean's work is very focused on craftsmanship and applies this to objects, installations and interiors. 

After briefly introducing his work, he asked us to individually go away and draw 6 physical objects that in some way relate to our projects - this was to create a reference point or "dictionary" of objects relevant to our subject matter. I split my 6 into two categories - privacy and personal information.

I stuck to fairly obvious objects relating to personal information originally - I.D cards, wallets and mobile phones all contain some form of personal information, with each containing slightly different pieces of information. For privacy, I went a bit more abstract and considered objects that symbolise control of their privacy in the physical world - closing curtains determines levels of visibility, locks are a symbol for securing and do not disturb signs limits interaction in some cases.

After presenting these back to Dean, he encouraged us to think a bit more and add anything else than came to us. I added sunglasses, a wardrobe and a hanger; specifically the hanger and the wardrobe were interesting to me as they are physical ways of storing identity - clothing makes up a big part of our physical identity. This exercise was really helpful as it helped me think a bit more outside the box.

After lunch, Dean asked us to think up 2 opportunities and 2 challenges which we then do a group brainstorm as a class to get everyone's opinions and insights on these questions. I used my two scenarios that I'd prepared last week - What if our personal information was standard currency and what if our physical identity was determined by our online identity - as my opportunities to explore through prototyping. 

When asking the class for help, I asked them to help me consider the second challenge about physical vs online identity, and how we could make our online identities physical. It was really nice to brainstorm with the class and get a lot of fresh perspectives and ideas that I might never have considered brainstorming on my own. 

Finally, Dean asked us to go off and draw up 4 ideas for potential prototypes to explore, which again, we would feed back to the class and get everyone's insights and opinions on. My 4 ideas were:

  • A twitter app that analyses tweets and sends text reminders to the user to remind them of their big 5 qualities
  • Redesigning the "Hello, my name is..." badge to put the user's social media accounts at the fore front instead of their real name
  • "The new debit card" which used personal information as currency and required the user to swipe their card whenever they used it, so they were aware of swiping away their information
  • The like box, which filled up with tokens based on any Facebook interaction - likes, friends, shares - that you were encouraged to fill up like a piggy bank.

When feeding back, the debit card got the most reception, so this is something I'll be keen to explore in the coming weeks. I was also planning to expand on my Twitter app to include Twilio to give it the text functionality, and maybe blend in the idea of the name badge to include the qualities returned by the Twitter app.

Overall, this was a really valuable and insightful day and it definitely made the transition from Find to Play a lot smoother.

MSc Product Design - Drawing a close to Find

With a strict goal in mind to keep 3 weeks for each stage, this week sees the drawing of the Find stage to a close - meaning that the bulk of my research is done and dusted.

To recap last week (week 2):

- I made a Python application that analyses personalities based on tweets from an active Twitter account. You can make your own one here.

- I sent out a questionnaire to gather some qualitative data on people's attitudes towards social media and internet privacy. While the information has been analysed, the questionnaire can be accessed here, while the general report of the results can be accessed here.

- I did a lot more reading, which I'll include a reading list at the bottom of the page.

This week, after a presentation by Linsey McIntosh where she talked about engaging people in our process, I decided to use the results from the survey to create personas. I was still struggling at narrowing down a specific target audience that I wanted to focus on and so Linsey suggested that personas would be a good start in narrowing down possibilities. From the results, the 3 personas I created were:

While these were completely fictional, I felt that they were successful in identifying who I should be targeting my product with. "Harry" was the strongest contender - it was people who would really benefit in partaking in conversation about his personal privacy that would get the most benefit out of my project. This was something to consider in my later steps of the process - I was keen to engage people like "Harry" in my Play and Make stages, possibly by doing workshops with them.

In terms of next step, play begins next week - my favourite stage. I'm looking into exploring RFID technology and expanding on my Twitter application. Meanwhile, I'd like to take these to the workshops potentially and begin engaging people in that step of the process. I've also been coming up with potential speculative design scenarios that I think would be interesting to create products in response too. The two that I've settled on for now are:


Things I read in week 2:

Digital Privacy is Making Antitrust Exciting Again -

The Transactional Self: Psychologist Jerome Bruner on Social Mutuality, the Paradox of Privacy, and How Storytelling Shapes Our Sense of Personhood -

From Invisible Ink to Cryptography, How the American Revolution Did Spycraft and Privacy-Hacking -

Why are some online extroverts not extroverted in the physical real world? -

What does it mean to be an introvert online? -

What does it mean when we need to take a break from Facebook? -

Facebook and Online Privacy: Attitudes, Behaviors, and Unintended Consequences -

Beware online "filter bubbles" -

Growing Up Wired -

Border Crossing The Premediation of Identity Management -

MSc Product Design - Twitter App + Personality Insights API

Taking a quick break from desk research, I decided to experiment with the Watson API and make my own personality analyser using Python and the Twitter API. Inspired by the demo by IBM for showcasing the Personality Insight API, I made a basic Python application that samples the latest 200 tweets of a desired public account, flatten them into a single string and pass them to the API. Returned is 5 qualities and their values based on the analysis of the 200 tweets. Here's how you can make your own.

Okay, so this is a little more than 5, but stick with me...

Okay, so this is a little more than 5, but stick with me...

First of, you'll need to set up a Python coding environment on your computer - I followed this guide to do this. I should point out now that this guide helps you set up to use Python3 on your computer when really we want to use Python2, but it also gives you steps on how to install the correct version of Python you'll need. The guide also sets you up to use the built in text editor Nano but you can use any text editor that registers Python - I use Sublime Text

Secondly, you'll need to create a Twitter application - you can do this here. Give it a name - I called mine MScPD-PersonalityInsightsTest - a description and a url (a placeholder one is fine). Don't worry about a callback URL for now - we're not looking to make this project live yet. Finally accept the T's & C's and your away.

Once your app is created, go to the keys and access tokens tab. Here you'll see your consumer key and your consumer secret - make a note of these since you'll need these later on. Scroll down the page and click the button to generate an access token. This will generate another two keys that you'll need later for the program to work. Finally make sure your access level is read and write.


Next, you'll need a IBM Bluemix account for access to the Watson API - you can sign up for one here. Once you're in the dashboard of the console, scroll down to the bottom of the page and click the create service button.

From the options, select Personality Insights from the Watson category. Give your service and name and leave it unbound for now, and choose the "lite" option. Once created, click the drop down menu to the right of your credentials - Credentials1 if you didn't change it - and click to the view them. This will reveal the key and password we need when we need our app to access the Watson API. Make a note of them, and that's you (almost) ready to start coding the app!

Before we start coding, we need to make sure we have access to the packages required, and we'll use Pip again just as we did earlier (if you followed the set up guide). In the terminal, enter:

This installs the twitter package we need...

This installs the twitter package we need...

...while this installs the package we need to interact with Watson.

...while this installs the package we need to interact with Watson.

With this installed, open up your text editor and enter the following:

These are the two main functions that makes the program work.

These are the two main functions that makes the program work.

This section calls the functions and prints the results into the terminal.

This section calls the functions and prints the results into the terminal.

The Python packages we import at the start are vital as they are dependencies for the python-twitter and watson-developer-cloudpackages we manually installed earlier. Without them, the python-twitter and watson-developer-cloudpackages won't function correctly.

When the analyse() function is called, it accesses the Twitter api via our app using the keys provided to gather the tweets we need from the Twitter handle we've selected - it gathers 200 tweets and excludes retweets so it's only interested in gathering what the user has tweeted. We then create an empty string to store the data we receive from Twitter and use an if statement to only include tweets that are in English and then encode them in UTF-8, which PI understands instead of Unicode, which Twitter understands.

The tweets are then pushed to PI - accessed via our credentials - who analyses the tweets and returns the data. By default, PI creates a tree structure for various categories. These categories are broken into Personality, Values, and Needs. These are then are broken into subcategories, and finally, broken into the the actual traits. We use the flatten() function to flatten the JSON structure that the analyse() function returns from PI.

We use the sorted() function to sort the results returned to us by PI. The results are sorted highest to lowest and show the 5 highest values according to PI based on the tweets. Finally, we then print the username of the account and the results to the console, and make sure to limit it to just 5 that we want to see.

Once you're finished coding and you're ready to run, open up your terminal again and type:

This will run your app in the terminal and feed back 5 traits and their values from the timeline of the selected handle!

And there we have it - my Big 5 traits based on my tweets!

And there we have it - my Big 5 traits based on my tweets!

Just for fun, I analysed the personality of a number of key figures:

Kanye West

Kanye West

Theresa May

Theresa May

Jeremy Corbyn

Jeremy Corbyn

Tim Brown - IDEO

Tim Brown - IDEO

While there's still a lot of tweaking left to do, I think there's a lot of potential for me to use this as part of my project further down the line. I'd experimented with trying to post the results to Twitter, but I've not figured out how to parse the information correctly into 140 characters. This is something I'm going to keep tweaking through out my project. Ideally I'd love to add functionality so that people can tweet the service and get a response back - I think this will see me heading down the Twitter bot route. 

Big shout out to Codecademy's tutorial on the Watson API for getting me started and Digital Ocean's tutorial for getting me set up working in the terminal properly. 

MSc Product Design - Independent Project #1

Beginning my final project, I decided to take a step back and review what I'd actually accomplished this year. In particular, I looked back at some of the other projects I'd undertaken that I'd maybe like to have revisited again and take another stab at with the additional time this project allowed. I'm largely aware that this is Honours Project Mk. 2 and I want my pièce de résistance of, not only my masters, but my uni career to be something exceptional. I was also really lucky and excited to have Martin Skelly as my advisor for this project.

These will probably be pretty wordy as I'm trying to cram as much into my weeks as I can - I've put a tl:dr at the bottom and attached all the links I've looked at this week.

After writing up about 11 different briefs and whittling it down to 5 (4 of which had been projects already undertaken this year) I finally settled on revisiting the privacy project - a total wildcard and it actually felt like coming full circle. Sort of finishing what you started. The issue we'd focused on originally was raising awareness of privacy and this was something I wanted to continue, albeit with my own spin on it.

Pretty quickly I found out that I was fascinated by the idea of online identity, and the value our personal data has for large corporations - especially Facebook and Amazon. In this day and age "our personal data is among today's most valuable information currency" and it's hard to determine what part of this is owned by companies, governments and obviously ourselves - provided it hasn't already been sold off by third parties.

Silicon Valley has already cornered the market on amassing personal information, and currently, Facebook's collection of data makes it one of influential organisations in the world. Very little is known however about what goes on "under the bonnet" of this machine despite the fact that users are feeding it the fuel it needs for free. As Vladan Joler, director the Share Foundation puts it:

"All of us, when we are uploading something, when we are tagging people, when we are commenting, we are basically working for Facebook,"

From this invaluable data that we provide to Facebook, they can then use complex algorithms to begin calculating and assigning characteristics to us. Ethnicity, sexual orientation, political affiliations and social classes - all of this can be gained through what we post directly to the platform and what we interact with. This information is then used by Facebook to push specific ads to us, based on our interests. We're sorted into various categories which advertisers can access to make sure their adverts are reaching their intended audiences. I found something fascinating here with this - how can our online activity and our online presence can be easily summarised into specific categories? Aren't we a lot more complex than that?

My "categories"

My "categories"

There's also a good article I read relating to how Facebook deals with ethnicity which can be read here. Basically, Facebook doesn't know if you're white or not.

This train of thought got me thinking about if there's any possible distinctions or similarities between our actual self and the online self perceived by the company's interpretations of you through the volunteered information. Are we the same online as we are in reality?

Fascinated by this, I touched on the work of Josh Cohen through an article called The Death of Privacy, who in his book The Private Life he sets the scene of a cultural currently in a "desperate psychological battle over the private self". Cohen talks about "life logging" which is the minute by minute transmission of data about one's life using any kind of social media platform or "quantified self technologies". Cohen mentions that life logging on digital platforms creates a memorable digital life, that contrasts our "irretrievable, transient life":

"Shadowing... is a permanent digital life... the digital recording becomes more 'real', more authoritative than your memory".

If this digital life is becoming more 'authorative', do our online selves actually then represent a more accurate and true version of us than what we present in reality? There's a couple of platforms I used to explore this - IBM Watson's Personality Insights and a website called

Both work in the same way - they analyse content posted on social media accounts and attempt to interpret the data to build a profile around you. The former was quite basic, relying on either a 100 word paragraph or linking up my Twitter account to provide them information while the latter was more advanced, sampling both Facebook likes and tweets to build a profile. The results of the two can be seen below:

IBM Watson's profile

IBM Watson's profile's profile's profile

Based on the results, for me felt a lot more accurate than the IBM profile, which suggests that my Facebook profile helps balance out certain big 5 qualities compared to the site sampling solely my tweets. This makes sense to me - on Facebook I would say I'm fairly conservative about what I post and like on Facebook where as I tend to use Twitter as a platform for sharing more abrupt thoughts. I'm definitely guilty as well of tweeting things I necessarily wouldn't say in public in an attempt to chase a few likes. 

Moving on from this week's desk research, I'm going to start looking ahead to identifying a key audience to focus on and tailor an experience for. As well as this, I'm going to start picking out more key insights and thinking about how I can use these to create product ideas centred around these insights - currently I'm excited about the idea of "information is currency" and "online identity vs offline identity".

Here's what I feel like after week 1 - only 9 more to go:

Tl:dr - personal information is one of the most valuable information currency in today's society, with many companies competing to gain the most data. Platforms such as Facebook and Google rely on us to volunteer the information to improve their services, but there's a huge grey area about what they are actually doing with your information. My project for this semester is focusing on raising awareness of this issue through the use of product design.

Things I've read this week:

Speculative Design -

The Death of Privacy -

How Facebook's tentacles reach further than you think -

Facebook doesn't know you're white -



Brain pickings articles -

Rise of the machines: who is the ‘internet of things’ good for? -

My own blog re: the privacy project at the start of the year - -

Personality Insights Demo -